How do I Difference Panel Data in R

Question

I am wondering if there is any easy R commands or packages that will all allow me to easily add variables to data.frames which are the "difference" or change of over time of those variables.

If my data looked like this:

set.seed(1)
MyData <- data.frame(Day=0:9 %% 5+1, 
                 Price=rpois(10,10),
                 Good=rep(c("apples","oranges"), each=5))
MyData

   Day Price    Good
1    1     8  apples
2    2    10  apples
3    3     7  apples
4    4    11  apples
5    5    14  apples
6    1    12 oranges
7    2    11 oranges
8    3     9 oranges
9    4    14 oranges
10   5    11 oranges

Then after "first differencing" the price variable, my data would look like this.

   Day Price    Good P1d
1    1     8  apples  NA
2    2    10  apples   2
3    3     7  apples  -3
4    4    11  apples   4
5    5    14  apples   3
6    1    12 oranges  NA
7    2    11 oranges  -1
8    3     9 oranges  -2
9    4    14 oranges   5
10   5    11 oranges  -3

Answer 1

ave

transform(MyData, P1d = ave(Price, Good, FUN = function(x) c(NA, diff(x))))

ave/gsubfn

The last solution can be shorteneed slightly using fn$ in the gsubfn package:

library(gsubfn)
transform(MyData, P1d = fn$ave(Price, Good, FUN = ~ c(NA, diff(x))))

dplyr

library(dplyr)

MyData %>% 
  group_by(Good) %>% 
  mutate(P1d = Price - lag(Price)) %>% 
  ungroup

data.table

library(data.table)

dt <- data.table(MyData)
dt[, P1d := c(NA, diff(Price)), by = Good]

Update

dplyr now uses %>% instead of %.% .

Answer 2

One can easily do it like this:

library(reshape2)
library(dplyr)

MyNewData <- 
 MyData %.%
 melt(id = c("Good", "Day")) %.%
 dcast(Day ~ Good) %.%
 mutate(apples  = apples - lag(apples),
     oranges = oranges - lag(oranges)) %.%
 melt(id = "Day", variable.name = "Good", value.name = "P1d") %.%
 merge(MyData) %.%
 arrange(Good, Day)

Regards